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Estimating the effect of background risk on individual financial choices faces two challenges.

Estimating the effect of background risk on individual financial choices faces two challenges. First, the identification of the marginal effect requires a measure of at least one component of human capital risk that qualifies as ”background” (a risk that an individual cannot diversify or avoid). Absent this, estimates suffer from measurement error and omitted variable bias. Moreover, measures of background risk must vary over time to eliminate unobserved heterogeneity. Second, once the marginal effect is identified, an evaluation of the economic significance of background risk requires knowledge of the size of all the background risk actually faced. Existing estimates are problematic because measures of background risk fail to satisfy the ”nonavoidability” requirement. This creates a downward bias which is at the root of the small estimated effect of background risk. To tackle the identification problem we match panel data of workers and firms and use the variability in the profitability of the firm that is passed over to workers to obtain a measure of risk that is hardly avoidable. We rely on this measure to instrument total variability in individual earnings and find that the marginal effect of background risk is much larger than estimates that ignore endogeneity. We bound the economic impact of human capital background risk and find that its overall effect is contained, not because its marginal effect is small but because its size is small. And size of background risk is small because firms provide substantial wage insurance.